In my eyes this is the brilliant idea. Just walk in, pick up what ever you want and leave. Get a milk or piece of bread and leave. All is automatically charged to your online account. What else ? You can comfortably put the staff back and go. You pay only what you take away. Great. What about the data collected behind. This is huge opportunity to optimize the process selling the product or even better the whole shopping cart to concrete person. Wow effect is right there.

Data about customers

I would like to talk mainly about this topic. In late 2013, I and my friends come with the idea about statistics from security cameras in retail stores. The goal is to recognize interest of your customers and optimize the offers, product placement and more based on the statistics taken from cameras. By comparison of the interest of the people and their behavior in segments (places) and compare to all others data like sales, promotions, advertising placement you can obtain interesting dependencies between data. The data valuable to solve the questions how to transform environment, product placement and also price even better than before to gain the revenue.

Amazon GO deal with the idea in different way. Just go behind all of this from different and better perspective. We would like to mainly bring something valuable for our customers.

No checkout required shopping.

You will never wait in line again.

Behind all these benefits is also huge amount of the data to transform and optimize environment and indoor outdoor advertisement. Track the goals. Experimenting with the advertisement to bring more people to concrete product, into the store and much more than we can ever imagine.

I love this idea from both perspective.

Amazon GO computer vision against RFID

The RFID gates that count what you take away are already here. They are not to much widely use and the main purpose is to use RFID for the security reasons. You can also track the customers and product movement in the environment based on RFID.
Why the RFID based checkout is not so widely used? You still need to pay somehow and this no line check out is not true as in case of Amazon GO.
But the main reason should be that the statistics about the customers are more valuable in case of use sensor fusion and optimize really everything. This is more valuable to retails and traders itself to invest into this technology and expand as much as possible.

This all make sense at a time of the big data, data driven everything, deep and machine learning progress than anytime before.

How does Amazon go works

System based purely on video from security cameras is not enough. Human vision without no others senses is not enough also. Basically the feature space to recognize actions, product and track concrete customers need better features. Features taken from more than one sensors. Technique which is called sensor fusion. There is also deep learning behind and other not so interesting staff :). There is lots of articles about this topics. Articles describing the Amazon patents and technical estimations of the technology.

I would like to point out something different. Some of my estimations and speculations.

Amazon go, cloud and deep learning

Amazon is strong in cloud computing. They are able to scale learning for large amount of the data on their own platform.
Point is that the evaluation of the learned model with multiple sensor input should be locally managed. Let say, collect data from all available sensors and calculate what is necessary for that service. Also, collect the features and send back to the cloud to improve the model. Learn the better one. Learn the model from the data taken from many stores from different kind of situations. Evaluate the model and provide increment back to improve the technology.

Even better provide the cloud service that distribute the learned model to any other who apply same sensors configuration as Amazon. This potential market Amazon go AS a Service for retail is potentially huge market. Really huge market.